Sustainable spatial planning for windfarms in Greece
Description
Scientific context Wind energy is the leading renewable energy source (RES) in Europe with installed capacity projected to double by 2040 [1]. In Greece, Wind Power Stations (WPS) cause high land take [2], and affect wilderness areas [3]. A sustainable scenario has been developed to resolve the WPS-biodiversity land conflict [4]. Here, we update the sustainable scenario (v3) [5] by adding all roadless islands and roadless areas over 5 km² to the WPS exclusion zone. The scenario applies to onshore wind energy investments: (a) operating wind farms and those with construction permits continue to operate for their lifetime nationwide; (b) all other planned WPS are considered only inside the potential investment zone (41% of Greece), where the national 2050 energy targets for WPS installed power (13 GW) are exceeded by 30%. Description The database includes three spatial layers: (a) exclusion zone (“green zone”; 59% of Greek land), (b) potential investment zone (“blue zone”; 41%), and (c) onshore wind turbines as point data (12,547 turbines as of 15/01/2025). The green zone (windfarm-free) comprises: (i) the terrestrial Natura 2000 network, (ii) the two least fragmented landscape classes (very low and low LFI; seff <10) outside Natura 2000, (iii) all roadless areas ≥5 km², and (iv) roadless islands and islets. In v4 the green zone has increased by 0.04% vs v3 data. The blue zone includes the remaining terrestrial areas outside Natura 2000 with higher fragmentation. All layers are in WGS84. This database (v4) is linked to Stefanidis, A., and Kati, V. (2026) Wind energy infrastructures drive habitat loss and fragmentation for threatened Orthoptera: spatial planning needed in developed landscapes. Biodivers Conserv 35, 151. https://doi.org/10.1007/s10531-026-03352-6 Significance, use, and limitations The database supports Strategic Environmental Assessment (SEA) for RES and broader spatial planning (e.g. energy, transport, tourism). It provides a horizontal planning guideline and does not replace Environmental Impact Assessments, Appropriate Assessments, or wildlife sensitivity maps. Intended users include investors, policymakers, authorities, NGOs, and the public. Minor spatial deviations may occur, particularly in insular areas, due to coastline mismatches among input datasets, including the roadless map used in v4. Funding A. Stefanidis was supported by the HFRI under the 4th Call for PhD Fellowships (grant 11266). References [1] WindEurope. 2025. https://windeurope.org/intelligence-platform/product/wind-energy-in-europe-2024-statistics-and-the-outlook-for-2025-2030/ [2] Kati et al. 2023a. JEM 348, 119340. https://doi.org/10.1016/j.jenvman.2023.119340 [3] Kati V. et al. 2023b. BiolCons 281, 110015. https://doi.org/10.1016/j.biocon.2023.110015 [4] Kati V et al. 2021. SCITOT 768, 144471. https://doi.org/10.1016/j.scitotenv.2020.144471 [5] Kati V. & Kassara C. 2021. Mendeley Data V3, https://doi.org/10.17632/kh3fjww93t.3
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Steps to reproduce
We used the following open-access geospatial datasets: 1. The roadless map of Greece (v2). Kassara et al. 2022. https://doi.org/10.17632/s6zh89fb5c.2 Date of access: 21/2/2025 2. Sustainable spatial planning for windfarms in Greece (v3). https://doi.org/10.17632/kh3fjww93t.1 Date of access: 20/2/2025 3. RAEWW (Regulatory Authority for Energy, Waste and Water): Geospatial Map for energy units & requests. https://geo.rae.gr/?lang=EN. Date of access: 15/1/2025 4. Digital Elevation Model from EUDEM 2016. European Digital Elevation Model (EU-DEM), version 1.1. https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1?tab=download.Date of access: 15/1/2025 5. Greek coastline. HNHS 2018. Greek coastline at scale 1:90000 (Last Update 22/10/2018). Hellenic Navy Hydrographic Service. https://www.hnhs.gr/en/?option=com_opencart&Itemid=268&route=product/product&path=86&product_id=271 Date of access: 15/1/2025 6. Natura 2000 network boundaries. https://ypen.gov.gr/perivallon/viopoikilotita/diktyo-natura-2000 Date of access: 15/1/2025. Step 1: We considered the roadless map of Greece (v2), and we filtered the polygons of roadless areas with an extent ≥5 km2, together with the Roadless Islands (RI) and Roadless islets (Ri) [dataset 1]. Step 2: We delineated the WPS exclusion zone (green zone excluding WPS applications) as the union of [dataset 1] with the former exclusion zone of the sustainable spatial planning for windfarms in Greece (v3) [dataset 2]. Step 3: We delineated the potential investment zone (blue zone allowing WPS applications) by subtracting the filtered roadless polygons from the former potential investment zone of the sustainable spatial planning for windfarms in Greece (v3) [dataset 2]. Step 4: We downloaded all wind turbines point data (12,547 turbines) from the RAEWW database [dataset 3]. We classified each turbine according to its permit licensing state: evaluation, production (with or without a Decision Approving Environmental Terms), construction, and operation. Step 5: We considered the Digital Elevation Model of Greece [dataset 4] to assign the elevation of wind turbines and classify them as below or above 1000 m elevation. Step 6: We defined the island vs mainland territory to classify wind turbines geography (island/mainland), considering the Greek coastline [dataset 5]. Step 7: We overlaid the points of wind turbines with the zones of the sustainable scenario (steps 2-3) to classify them as falling in the green or blue zone. Step 8: We overlaid the points of wind turbines with the Natura 2000 network [dataset 6] and classified them as inside or outside the network. Step 9: We uploaded the turbines’ classification information (steps 4-8) to the onshore wind turbines geospatial file.
Institutions
- University of IoanninaEpirus, Ioannina